Theories, Detection Methods, and Opportunities of Fake News Detection

Abstract

Internet has been popularized in recent years in the whole world, and it makes world more closer virtually. The risk of spreading fake news is also increased in proportion of Internet growth because it is very easy to spread a wrong news on social cites [1, 2]. A person has more access to other people through social cite, and a fake news easily can spread in a short span of time. So to deal with this problem, there are many big companies that are working on new algorithms to detect and stop fake news on social cites. So we have tried different models to detect fake news and compare results of different models on a data set of news article [3]. In this particular paper, we proposed a long short-term memory (LSTM) framework to detect fake news, and it shows a comparison between different models.